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灰色系统理论的多目标可靠性稳健设计
引用本文:张瑞军,邱继伟,贾庆轩.灰色系统理论的多目标可靠性稳健设计[J].北京邮电大学学报,2014,37(3):23.
作者姓名:张瑞军  邱继伟  贾庆轩
作者单位:1. 山东建筑大学 机电工程学院, 济南 250101;
2. 北京邮电大学 自动化学院, 北京 100876
基金项目:国家自然科学基金项目(51075244);山东省教育厅计划项目(J12LB60)
摘    要:通过对目标函数和约束条件进行灵敏度分析,生成目标函数和约束函数的灵敏度附加项,提出了2种基于灵敏度附加目标函数的可靠性稳健优化设计模型;针对不同评价者对目标获取信息的局限性,基于灰色系统理论把评价者对目标的评估分配在一定范围内,给出了计算各目标函数权重系数的专家评估方法. 应用Matlab7.1语言的优化工具箱和符号工具箱实现圆柱螺旋压缩弹簧的多目标可靠性稳健优化设计. 算例表明,该方法具有较高的精度和可靠度,为机械零件的可靠性设计提供了理论依据.

关 键 词:多目标优化  灰色系统理论  灵敏度设计  可靠性稳健设计  
收稿时间:2013-08-12

Multi-Objective Robust Design for Reliability Based on Grey System Theory
ZHANG Rui-jun,QIU Ji-wei,JIA Qing-xuan.Multi-Objective Robust Design for Reliability Based on Grey System Theory[J].Journal of Beijing University of Posts and Telecommunications,2014,37(3):23.
Authors:ZHANG Rui-jun  QIU Ji-wei  JIA Qing-xuan
Affiliation:1. School of Mechanical and Electronic Engineering, Shandong Jianzhu University, Jinan 250101, China;
2. School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China
Abstract:Additional items of sensitivity of objective and constraint functions are generated through analyzing the corresponding functions objective functions and constraints. Two models of optimization design for reliability are proposed based on the additional items of sensitivity. According to the limitations of information for objective functions obtained from different evaluators, the objective functions and the evaluators' assessment based on gray system theory was allocated in a certain range. The expert assessment method is presented to calculate the weight coefficients of the objective functions. Reliability-based robust optimization design of cylindrical helix spring is achieved by using the optimization toolbox and symbolic toolbox of Matlab. Numerical examples prove that the proposed approach which provided the theoretic basis for the reliability design of the mechanical elements has a higher precision and reliability.
Keywords:multi-objective optimization  grey system theory  sensitivity design  reliability-based robust design  
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